Residential Demand Side Management Using Artificial Intelligence
Ajith Vijayan, Venugopalan Kurupath, Jani Das
Abstract
Ajith Vijayan, Venugopalan Kurupath, Jani Das
Abstract
There is an exponential increase for the global electricity demand during the last decade owing to overall development, especially in the industrial sector. Demand side management (DSM) is a critical function of a grid that encourages users to make decisions about their energy usage and enables energy suppliers minimize peak demand and reshape the profile of load. Energy demand could be minimized at specific time intervals using grid control algorithms like DSM. It is planning, implementing, and monitoring activities of electrical utilities which encourage consumers to modify their level and pattern of electricity usage, ensuring stability on the electricity grid and balance the electrical demand throughout the year. This paper presents a load shifting demand side management which transfers low priority consumer loads from peak to off peak periods, which can reduce peak demand and thereby cost. Simulations are carried out for a residential infrastructure. The results show that significant cost savings are achievable with the proposed optimization strategy.
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There is an exponential increase for the global electricity demand during the last decade owing to overall development, especially in the industrial sector. Demand side management (DSM) is a critical function of a grid that encourages users to make decisions about their energy usage and enables energy suppliers minimize peak demand and reshape the profile of load. Energy demand could be minimized at specific time intervals using grid control algorithms like DSM. It is planning, implementing, and monitoring activities of electrical utilities which encourage consumers to modify their level and pattern of electricity usage, ensuring stability on the electricity grid and balance the electrical demand throughout the year. This paper presents a load shifting demand side management which transfers low priority consumer loads from peak to off peak periods, which can reduce peak demand and thereby cost. Simulations are carried out for a residential infrastructure. The results show that significant cost savings are achievable with the proposed optimization strategy.
Key concepts: Smart grid, Electricity, Peak demand, Grid, Load management, Energy management, Demand management, Computer science